The　classification　and　dynamics　monitoring　of　wetlands　using　remotely　sensed　data　is　a　complicated,　time-consuming　process　involving　high　costs,　and　the　accuracy　varies　depending　on　the　techniques　used　for　image　processing　and　analysis,　and　the　time　and　costs　required　for　training,　etc.　This　paper　presents　an　optimization-based　layered　classification　method　for　the　classification　and　dynamics　monitoring　of　wetlands　based　on　a　decision　procedure　of　multiple　objectives.　Four　driven　factors　including　techniques　to　be　used,　classification　accuracy,　and　the　time　and　cost　needed　for　the　classification,　were　selected　as　the　indicators　of　criteria　in　optimization　of　the　layered　classification.　This　method　was　applied　to　Thematic　Mapper　(TM)　image　classification　of　the　wetlands　in　Minjiang　River　estuary　and　led　to　the　overall　correct　percentage　of　85.13%　for　seven　categories　of　the　wetlands.